Hi there,
I'm doing some RFM (recency, frequency, monetary) and gap (lapsed period) analysis on constituent segments in the database and wondering if anyone has done the same. I'm especially interested in gap analysis as I'd like to look at number and length of lapse periods (years off) during a customers time with us. Currently looking at ticket buying behaviour but will use it on donations once I've worked out the kinks.
Cheers
H
Heath Wilder
I've done some experimenting with recency, frequency and total monetary value (tickets + contributions). I end up creating a set of Tessitura ranks one for each category. The ranks were decile over a 5 year period within a constituent type. So comparing schools with other schools, corporations vs corporations, individuals vs individuals. This produced a number for each of the ranking groups between 0 and 10 (0 meaning that there were no values in the last 5 years for this customer). With 1 being the least advantageous value and 10 the most advantageous value. Therer's a final value that was a sum of the other scores so that value was between 0 and 30. The intent here was to get broad groupings of accounts in a way that would be understandable by staff around the building.
Thanks I used an ntile function to break up BI.VT_ORDER_DETAIL (removing comps and non performance orders) into 3 quartiles. I love the idea of rolling in / separating contributions out to get a Customer Lifetime Value estimate. That final value score is definitely something that I'll take a look at. I'll raise that as a topic at Analytic Coffee